Week 9 Progress Report

I have finally completed my whole science assessment ! I've finally accomplished something that I thought would be a real challenge and turned it into a great learning experience that I can bring with me into my future in science. I personally loved working on the SRP , as it involved making a blog , writing up a report and make bubbl.us mind maps , which is definitely more enjoying than sitting an exam. I'm happy that I stuck to my timeline , if not , I know I would have gone off course and know I wouldn't have finished this project to the best of my ability . In about a weeks time I will have to hand in my report , along with sending my blog link and bubbl.us link to my science teacher . Overall i'm very proud of myself and hopefully that will be reflected in my mark. Anyways goodbye now my blog , i've had fun working with you ! :)




BUBBL.US: 

Click on mind map and press 'View', then press 'zoom in' on top toolbar to enlarge.

Week 8 Progress Report: Holidays

For the past week , I have finally edited , printed and stapled my Scientific Report , already to give to Mr.Ng to read over when I get back from my holiday break. I am very happy that I have finished my report , all I need it to write my last blog post with my bubbl.us link , then I will be completely done.

Week 7: Holidays

This week , I looked over my report and all the pages in my blog that I have done so far for anything that I have to add that I might have missed out on or things that I may need to take out that weren't necessary for the assessment . I'm proud of what I have done so far.  I have also made sure all my bibliographies are completed for everything I have used as help for my assessment.

Week 6: Conclusion

From this experiment , where the aim was to determine  which brand of microwave popcorn brand yields fewer un-popped kernels. The data gathered in this experiment  firstly gave unexpected results.Although determination was successful, It was found that my hypothesis of ,   If the cost of a microwave popcorn brand is higher then it will yield fewer un-popped kernels, was incorrect. As results proves that Uncle Toby's, the most expensive(high priced name brand) had the highest average total percentage of popped kernels with 91 %, closely followed by Coles, the cheapest brand (sure fine generic brand) with 88 % and lastly Poppin with lowest percentage (mid range name brand) with a drop to 78%.  It is , however, interesting to note that although Coles (The sure fine generic) brand had the second highest percentage , it would be of better value for your money than the Uncle Toby's brand with the highest brand as it was a lot cheaper and more consistent with results overall in terms of the number of un-popped , popped and total kernels in each bag, based on results. The relevance of these findings is to help Popcorn companies understand any improvements they need to make to improve the structure and "pop-ability" of popcorn , to rid the name of "the old maids" which refers to an unpopped kernel in a batch of popped popcorn kernels. By knowing the percentage of popped kernels in the bags will help for them to focus on the rest of un-popped kernels, this would definitely prove profitable for their business and improve the current decreasing popcorn sales. 


BUBBL.US UPDATE:

Week 6 Progress Report

I have almost finished my SRP blog. I have achieved more than I expected I would have thought for my assessment , which I can say I am very proud of.

In week 6 of my SRP , I have finally have written my conclusion , which I have also inserted into my report. In my conclusion I have brought together all my results and findings and also keeping in mind not to introduce any new data and information. I use the marking criteria on the myclassess website as a guide for writing my conclusion, it helped myself a great deal.  

My conclusion will be featured in the blog following this one.

As for the current update on my report , I have proof read through what I have so far , fixing any mistakes and making sure it follows the outline of a proper Scientific Report. Hopefully this week I will be able to send my report to my Teacher , Mr.Ng so he can also have a look over it.

Week 5: Discussion

I have worked very hard and put a great amount of effort into my "Discussion" with my experiment , making sure it meets the assessment criteria.


Discussion

In my experiment, where my aim was to determine  which brand of microwave popcorn brand yields fewer un-popped kernels- From carrying out this experiment many results were collected, that if  analysed, reveal obvious patterns and trends. Firstly, when comparing the results of the total percentage popped kernels of each brand, that the results are fairly close, as for the total percentage of un-popped kernels popped follow this trend of being fairly close in results as well. Uncle Toby’s brand was the most expensive , followed by Poppin and then the sure fine generic brand , Coles. Some results seemed to be inconclusive, and unconvincing.When popcorn bags were tested individually and repeated three times for each brand, Uncle Toby’s and Poppin had very dispersed amounts of un-popped kernels , with Poppin’ having an outlier of 269 kernels. Unlike Coles , which had a very consistent amount of un-popped kernels all in the 50’s range.  As for popped kernels for each brand stayed consistent , besides for Poppin which had an outlier result of 272, although when these results are calculated by their mean , they are clustered and are very closely tied. Each popcorn bag  contain an average of total kernels , ranging from 469 to 542. In all cases , more than 50% of the kernels popped and in most cases 80% or more.In no cases, 100 % or the popped kernels actually popped.

Results in this experiment were achieved by collecting  raw data onto two separate data tables on a data sheet.Then collaborating my results, I divided the total number of popped kernels in each brand by the total kernels for each brand, obtaining a percentage of popped kernels produced by each brand to graphs ( One being a column graph recording total average percentage of popped kernels and a stacked column graph also showing this as well as total average percentage of un-popped kernels. By counting the total amount of both popped and un-popped kernels I easily accounted for any difference between each brand. Using the measurement of percentages of popped kernels allowed myself to have a more accurate comparison of the brand's overall performance. From this , I was able to see if my background research backed up my results . In this case it did ,  the Poppin bag with outlier results, has a poor ordered crystallite's arrangement of the cellulose molecules in it’s kernels, as popcorn’s popping quality is determined by this, which can happen on occasions and having a poor crystallite structure may have meant it needed more time to cook. Not only that , I came to the agreement that all three brands have a similar “pop-ability” , with alike crystallite structures , referring back to there average amount of popped kernels or Two other explanations exist for kernels which do not pop at proper temperatures, known in the popcorn industry as "old maids". The first is that un-popped kernels do not have enough moisture to create enough steam for an explosion. The second explanation, according to research led by Dr. Bruce Hamaker of Purdue University, is that the un-popped kernel may have a leaky hull. In no cases, 100 % or the popped kernels actually popped. From research and my own belief that microwaves heat from the outside in , the chances are that the kernels that didn’t pop , were the one closest to the middle of the packet therefore , would be the last to receive heat. To get those middle kernels to pop , you’d have to sacrifice the quality of the kernels already pop as the extra heat would cause them to burn and spoil the product. All this research proves to have supported the reasons for my results and findings , especially ones I though were inconclusive and questionable.

Conferring  the reliability and validity of the experiment ,it can be said to be a very reliable and valid source to obtain conclusions from. There could have been a possible problem for my internal validity of my experiment if I decided to incorporate anything besides the independent variable, this could have had an affect on the result of the dependant variable in my experiment. A solution for this problem I  carried out was that I undertook to decrease the threat of internal validity by using the following strategies to keep my experiment valid and reliable. To obtain consistent results , I popped three bags of each of the three brands. I waited ten minutes between each popping in order to eliminate oven pre-heating. Not only that, the same microwave oven was used, same cooking. temperature and cooking time was used to cook each bag of microwave popcorn. To terminate any discrepancy among the total sum of kernels in each brand, I used a percentage of popped kernels to total sum of kernels for each brand. Additionally, all popcorn bags were purchased at the exact same time and I tried my best to keep the expiration dates as close to each other as possible to eliminate the age of popcorn as a possible variable.

Although my experiment gained appreciable results , there are always ways in which it can be bettered.  Various improvements that could be put into place include to test more than three brands of microwave popcorn , possibly another high brand , mid-range and sure fine generic brand along with the other three brands I tested for further representative and reliable results. I could also test each brand of microwave popcorn more than three times , I would suggest testing out each brand at least five times, this would be an improvement of the experiment I carried out as one of it’s weaknesses was that some results were very dispersed and more testing on each brand could improve results . The more times an experiment is replicated with the same results; the more valid the hypothesis becomes. An additional amendment that could be made would be would be to discuss your experiment design with an “expert/s”, as they could help with any errors that you had not seen in your experiment on your own and they may also suggest anything that might need to be also included into your experiment. An expert may suggest that you investigate related topics that you didn’t think of yourself, this was one of my experiments weaknesses as I haven’t seen my teacher enough and asked all questions I was unsure about.  Another weakness i encountered while carrying out this experiment that the popcorn did get messy and I had no where to store all 900 grams of popcorn , So a suggestion for further tests would be to pour the popcorn into a large bowl and sort the popped kernels back into the popcorn bag and the kernels into a smaller bowl , so the popped kernels were neatly stored and could be eaten later or easily disposed like the un-popped kernels. Next time , I could also consider using a different microwave with a different energy usage , or a different cooking time , which I suggest could be longer , to test if more kernels will be popped.

To conclude my discussion , I would say that many of both patterns and trends can be observed from the experimental results that were gathered from this investigation. Background research information was crucial factor prior the the assessment task to match and explain why this information may have not have supported the findings. While the experiment is in all cases reliable and valid it also had weaknesses and can be suggested improvements to better the carrying out this experiment and future cases. 

• • BUBBL.US UPDATE:
    

    

    
    

Week 5 Progress Report

It is now week 5 for my SRP. I have achieved a considerable amount of work this week. I have completed evaluating my method , my discussion , reading over and editing my research paper and writing up my purpose and hypothesis  into my  report in my NeoOffice Document.


Hypothesis


  If the cost of a microwave popcorn brand is higher then it will yield fewer un-popped kernels.




Purpose
The purpose of this investigation is to assess which brand of microwave butter flavoured popcorn yields fewer un-popped kernels. This question had the need to be answered from both general interest on popcorn itself in terms of why it pops, why some kernels don't pop and it's best popping conditions and the other reason being, to find out which popcorn I should purchase in future, as I believe un-popped kernels represent un-wanted value for your money.








Analysis 
To analyse my data , I have answered a Data Analysis Checklist and hav evaluated on it following it.

There is sufficient data to know whether my hypothesis is correct. 


The data that I have collected in my experiment is indeed accurate.  As the methods of collecting data are both reliable and valid , ensuring data I attain from carrying out this experiment will be accurate.


I have summarised my data with an average where appropriate , I have clearly executed this in my second table (Table 2) of my results , as 3 brands of butter flavoured microwave popcorn were tested 3 times each and in order to  organise results into a form which was able to be graphed .


My Chart does specify units of measurement for all data , as all quantitative data was sorted into two tables with appropriate units of measurement (Table 1 and Table 2) found in the Results Section of my experiment.  Additionally , the graphs use the unit of measurement of percentage for both graphs.


I have verified that all calculations are correct. All calculations were fulfilled with a Scientific calculator and checked 3 times , in order to make sure mistakes were not present in the data. Any calculations that were not whole numbers were rounded to the nearest whole number. 


Evaluating my method 
Once my experiment was completed , before I wrote up my conclusion, I reflected over my method of collecting data. In the beginning of this task in week 3, I have stuck with my method of collecting data which was as stated below.


The method I will be using to collect data for the purpose of this study will be that any single kernel that either fits in the criteria of either being:

•  Partially broken  
•  unbroken but inedible 
•  Not fully popped

Kernels that fit in this criteria will be considered un-popped. Other kernels must be fully popped to be counted as a popped kernel. Once all the bags are popped, I will then individually count the popped and un-popped kernels, placing the un-popped kernels in a small bowl and the popped kernels in a larger bowl. After this I will record the raw data onto two separate data tables on a data sheet.Finally to collaborate my results, I divide the total number of popped kernels in each brand by the total kernels for each brand, obtaining a percentage of popped kernels produced by each brand to graph. By counting the total amount of both popped and un-popped kernels I can easily account for any difference between each brand. Using the measurement of percentages of popped kernels will allow myself to have a more accurate comparison of the brand's overall performance.  After much deliberation between constructing a pie graph  or column (bar) graph , I have decided to go ahead with the column graph to record my results as not only are they easy to understand , because they consist of rectangular bars that differ in height or length according to their value, They also will be easier to identify any trends and patterns in the results.  . This method will be easy to follow along with and repeat. 


But, at around week 2 , when I was planning out what methods of collecting data , It was hardly what I stated above. It was a lot simpler and didn't have as much thought in relations to making sure I got the best results possible to identify any trends and patterns in the results that I can use for my discussion and conclusion after the experiment was carried out , it also lacked reliability and validity. 

This was my very first draft of what I had in plan for my "method of collecting data".

At about Week 3 within the SRP project , when I started to construct my Scientific Method and designing my experiment, I had a clearer view of what was required of my experiment and it's requirements. I then took my ideas from week 2 and collaborated them into a computerised copy of my "method of collecting data".

Column graph template for experiment

BRAND	POPPED KERNELS	UN-POPPED KERNELS	TOTAL KERNELS
Uncle Toby’s 1
Uncle Toby’s 2
Uncle Toby’s 3
Poppin 1
Poppin 2
Poppin 3
Coles 1
Coles 2
Coles 3

 Table template for experiment

But towards the end of week 3 of My SRP , I had come to a problem. The table didn't collect all the data I needed. So I decided to create a second table which I would fill out once I had finished collecting my data from the first table which was named "Table 1" and the one I was creating would be , "Table 2". Additionally , I also had a think about the graph I was using . As I was using the graphing program to make the template of my Column Graph , I experimented with other graphs to see if it would do better off with my experiment. I saw the "Stacked Column Graph" and looked up on their purpose, which is to compare contribution of two or more variables to a total , across X-azis categories or time.  I planned on using a 100% stacked column graph plot option, where the values selected variables will be normalised and scaled to 100 %. I planned to use this type of graph to show the percentage of average popped kernels to un-popped kernels when put over it's average total.I was proud of my new discovery and thought this would be really helpful in comparing results.

Stacked Column Graph Template for experiment

BRAND	AVERAGE NUMBER OF POPPED KERNELS	AVERAGE NUMBER OF UN-POPPED KERNELS	AVERAGE TOTAL KERNELS	TOTAL PERCENTAGE OF POPPED KERNELS(%)
Uncle Toby’s
Poppin
Coles

 Table 2 Template for experiment

I had finally come up with my method of collecting data and was very satisfied with it and was ready to use these methods for my experiment , and they were deemed successful and have been put into my report.

As for my scientific method, I have done a lot of progression work on it. I had problems with it in the start , where I had about 10 steps which definitely did not include all steps required to successfully achieve the experiment with ample results. At the start my Scientific method did not start each step with a "verb" which was a disadvantage to someone trying to carry out the experiment , so I imagined that when I read out my Scientific method , I was instructing these steps to someone else carrying out the experiment , this really helped me to see if I had to alter my method in anyway for it to be easy to understand for everyone. In the end I came up with a 15 step Scientific Method which executed the experiment in a safe and successful way , where I got ample results.

From all of this I have learnt that selecting the right method involves many factors. Some methods are better for gathering quantitive data, others for qualitative data. Some are better for particular audiences than other. Some Methods gather riches, deeper data than other do.

Final Scientific Method

1.Make sure you have all your equipment prepared to use

2.Prepare data sheet

3.Choose one bag of popcorn and remove from plastic packet and dispose in bin.

4.Unfold popcorn bag and place  flat down on microwave plate.

5.Close microwave door.

6.Set timer to 2 minutes and press start.

7.Wait until times goes off and open microwave door.

8. Time 10 minutes from when you open the microwave door using a timer or stopwatch.

9.Once this time is up , Take out popcorn bag from microwave and open the bag.

10. Sort the popcorn individually into either the small bowl for the un-popped or the big bowl for the popped popcorn.

11.Count how many un-popped kernels and popped kernel there are and record into the first table (table 1)

12.Repeat steps 3-11 for the remaining bags of popcorn

13. Calculate the average number of popped, un-popped, and total kernels for each brand of popcorn by adding the data recorded for that brand and record in second table (table 2), after all bags are popped and recorded.

14.Divide the number of popped kernels by the number of total kernels to find the percentage of popped kernels for each brand and record results in the second table (table 2) and graph results in column graph and stacked column graph like the ones listed below.

15.Compare Results.

My discussion will be in my next post.

BUBBL.US UPDATE: